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With billions of people facing moderate or severe food insecurity, the resilience of the global food supply will be of increasing concern due to the effects of climate change and geopolitical events. In this paper we describe a framework to…
This study proposes an approach for predicting the impacts of scenarios on food security and demonstrates its application in a case study. The approach involves two main steps: (1) scenario definition, in which the end user specifies the…
We introduce a new measure for fair and meaningful comparisons of single-valued output from artificial intelligence based weather prediction (AIWP) and numerical weather prediction (NWP) models, called potential continuous ranked…
The world is becoming more globalized every day and people can buy products from almost every country in the world in their local stores. Given the different food and feed safety laws from country to country, the European Union began to…
Rice is a staple food in the world's diet, and yet huge percentages of crop yields are lost each year to disease. To combat this problem, people have been searching for ways to automate disease diagnosis. Here, we extend on previous…
In a pandemic like Covid-19, there are many countries of lower-earning cannot provide a complete locked-down within the duration of the detected case. The locked-down may result in famine throughout the region of underdeveloped countries…
The proliferation of intermittent distributed renewable energy sources (RES) in modern power systems has fundamentally compromised the reliability and accuracy of deterministic net load forecasting. Generative models, particularly diffusion…
Intelligent systems are increasingly integral to our daily lives, yet rare safety-critical events present significant latent threats to their practical deployment. Addressing this challenge hinges on accurately predicting the probability of…
Agricultural production is highly dependent on naturally occurring environmental conditions like change of seasons and the weather. Especially in fruit and wine growing, late frosts occurring shortly after the crops have sprouted have the…
Climate change is expected to increase the likelihood of drought events, with severe implications for food security. Unlike other natural disasters, droughts have a slow onset and depend on various external factors, making drought detection…
Advancing models for accurate estimation of food production is essential for policymaking and managing national plans of action for food security. This research proposes two machine learning models for the prediction of food production. The…
Sepsis is a life-threatening infectious syndrome associated with high mortality in intensive care units (ICUs). Early and accurate sepsis prediction (SP) is critical for timely intervention, yet remains challenging due to subtle early…
Governments have to supervise and inspect social economy enterprises (SEEs). However, inspecting all SEEs is not possible due to the large number of SEEs and the low number of inspectors in general. We proposed a prediction model based on a…
Monitoring tools for anticipatory action are increasingly gaining traction to improve the efficiency and timeliness of humanitarian responses. Whilst predictive models can now forecast conflicts with high accuracy, translating these…
Climate change is becoming a widely recognized risk factor of farmer-herder conflict in Africa. Using an 8 year dataset (Jan 2015 to Sep 2022) of detailed weather and terrain data across four African nations, we apply statistical and…
Drought threatens food and water security around the world, and this threat is likely to become more severe under climate change. High resolution predictive information can help farmers, water managers, and others to manage the effects of…
Global food security depends on predicting crop responses to climate variability, yet process based crop models remain too computationally expensive for large scale exploration of genotype and environment interactions. Here we develop a…
Although the widespread use of AI systems in today's world is growing, many current AI systems are found vulnerable due to hidden bias and missing information, especially in the most commonly used forecasting system. In this work, we…
Space weather events may cause damage to several fields, including aviation, satellites, oil and gas industries, and electrical systems, leading to economic and commercial losses. Solar flares are one of the most significant events, and…
The increase in renewable energy sources (RES) has reduced power system inertia, making frequency stabilization more challenging and highlighting the need for fast frequency response (FFR) resources. While building energy management systems…